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spfilteR  

Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models
View on CRAN: Click here


Download and install spfilteR package within the R console
Install from CRAN:
install.packages("spfilteR")

Install from Github:
library("remotes")
install_github("cran/spfilteR")

Install by package version:
library("remotes")
install_version("spfilteR", "2.2.0")



Attach the package and use:
library("spfilteR")
Maintained by
Sebastian Juhl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-12-07
Latest Update: 2025-02-21
Description:
Tools to decompose (transformed) spatial connectivity matrices and perform supervised or unsupervised semiparametric spatial filtering in a regression framework. The package supports unsupervised spatial filtering in standard linear as well as some generalized linear regression models.
How to cite:
Sebastian Juhl (2020). spfilteR: Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models. R package version 2.2.0, https://cran.r-project.org/web/packages/spfilteR. Accessed 04 Jun. 2026.
Previous versions and publish date:
1.0.0 (2020-12-07 10:20), 1.1.0 (2021-05-13 01:00), 1.1.1 (2021-10-05 11:00), 1.1.2 (2022-01-18 08:50), 1.1.4 (2022-03-09 10:40), 1.1.5 (2022-08-22 21:00), 2.0.0 (2025-01-22 15:10), 2.1.0 (2025-02-21 14:30)
Other packages that cited spfilteR R package
View spfilteR citation profile
Other R packages that spfilteR depends, imports, suggests or enhances
Complete documentation for spfilteR
Functions, R codes and Examples using the spfilteR R package
Some associated functions: MI.decomp . MI.ev . MI.resid . MI.sf . MI.vec . fakedata . getEVs . glmFilter . lmFilter . partialR2 . vif.ev . vp . 
Some associated R codes: MI.decomp.R . MI.ev.R . MI.local.R . MI.resid.R . MI.sf.R . MI.vec.R . fakedataset.R . getEVs.R . glmFilter.R . lmFilter.R . methods.R . partialR2.R . utils.R . vif.ev.R . vp.R .  Full spfilteR package functions and examples
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